Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, "Estimation of the Hydrodynamic Performance of the Parameterized Hull Forms Using Deep Learning", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10
Abstract | The CFD (Computational Fluid Dynamics) analysis is normally used to evaluate the hydrodynamic performance of hull forms in the process of hull form design. The hull form candidates are improved through the iterative process of editing them if their performance is not good enough. However, since the CFD analysis is computationally expensive, the estimation of the hydrodynamic performance using it requires a long time. Due to the limited time for the design, the hull form iterations are not enough to find the optimal hull form. To solve this problem, we proposed a method to estimate the hydrodynamic performance of the hull forms using deep learning. The use of deep learning has the disadvantage that it takes a long time to accumulate data and learn but has the advantage that it takes only a very short time to run the model and obtain the result once training is complete. In this study, the hull form of a small ship was first parameterized with dozens of parameters to generate various hull forms. Then, a number of hull forms were created by randomly generating thousands of parameter sets that determine the hull form. Finally, the hydrodynamic performance for the ground truth was derived by performing CFD analysis on the hull forms. We considered multiple deep learning models to estimate the performance more accurately and selected the best model among them. The proposed method was applied to a small ship. As a result, with the proposed model, the hydrodynamic performance of the hull forms can be estimated shortly with a certain level of error. |
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Publication Date | 2022-11-06 |
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Yeongmin Jo, Myung-Il Roh, Hye-Won Lee, Donghun Yu, "A Ship Tracking Method under Dynamic Characteristic Changes with LSTM", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10
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In-Chang Yeo, Myung-Il Roh, Hye-Won Lee, "An Optimization Method of the Surround-View Camera System for Automatic Berthing of Ships", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10
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Do-Hyun Chun, Myung-Il Roh, In-Chang Yeo, "Optimum Design of Membrane-type LNG Tanks for Installing Insulation", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10
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Min-Chul Kong, Myung-Il Roh, Jisang Ha, Jeong-Ho Park, EunSeok Jin, Donghun Yu, "Integrated Navigation Assistance System Using Augmented Reality", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10
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송하민, 노명일, 하지상, 김기수, "해군 함정의 승조원 구성 시뮬레이션 방법", 2022년도 대한조선학회 추계학술발표회, 창원, 2022.11.09-11
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박정호, 노명일, 이혜원, 조영민, 손남선, "딥 러닝 기반 다중 카메라 영상을 이용한 해상 장애물 탐지 추적에 관한 연구", 2022년도 한국항해항만학회 추계학술발표회, 부산, pp. 186, 2022.11.10
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정동근, 노명일, 여인창, 공민철, 김기수, 이준식, 유원철, "다양한 해상 객체를 반영한 소형 선박의 항로 계획법", 2022년도 대한조선학회 추계학술발표회, 창원, 2022.11.09-11
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공민철, 노명일, 이혜원, 전도현, 조영민, 박정호, "자율 운항 기술 검증을 위한 VR 기반 시뮬레이션 프로그램", 2023년도 한국CDE학회 동계학술발표회, 평창, pp. 48, 2023.02.08-11
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여인창, 노명일, 이혜원, 유동훈, "선박용 서라운드 뷰 영상의 자동 생성 방법", 2023년도 한국CDE학회 동계학술발표회, 평창, pp. 45, 2023.02.08-11
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하지상, 노명일, 공민철, 김기수, "격벽, 장비 및 배관을 고려한 선박의 배치 설계 방법", 2023년도 한국CDE학회 동계학술발표회, 평창, pp. 8, 2023.02.08-11